Point Cloud Registration Algorithm Based on Angle Constraint and Maximal Clique

[2] Liu T B, Guo J H, Song Y B et al. Preoperative and intraoperative cross-source point cloud registration based on attention mechanism enhancement[J]. Chinese Journal of Lasers, 52, 0307103(2025).

[3] Li Z Q, Zhang Y, Xiong F L et al. Laser simultaneous localization and mapping algorithm based on optimized ground segmentation and closed-loop detection[J]. Acta Optica Sinica, 44, 2015001(2024).

[4] Li J W, Zhan J W. Review on 3D point cloud registration method[J]. Journal of Image and Graphics, 27, 349-367(2022).

[5] Besl P J, McKay N D. A method for registration of 3-D shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14, 239-256(1992).

[6] Segal A, Haehnel D, Thrun S. Generalized-ICP[C](2009).

[7] Yang J L, Li H D, Campbell D et al. Go-ICP: a globally optimal solution to 3D ICP point-set registration[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, 2241-2254(2016).

[8] Koide K, Yokozuka M, Oishi S et al. Voxelized GICP for fast and accurate 3D point cloud registration[C], 11054-11059(2021).

[9] Yang Y L, Li J Y, Wang Y et al. Point cloud registration algorithm based on NDT and feature point detection[J]. Laser & Optoelectronics Progress, 59, 0810016(2022).

[10] Aiger D, Mitra N J, Cohen-Or D. 4-points congruent sets for robust pairwise surface registration[J]. ACM Transactions on Graphics, 27, 1-10(2008).

[11] Mellado N, Aiger D, Mitra N J. Super 4PCS fast global pointcloud registration via smart indexing[J]. Computer Graphics Forum, 33, 205-215(2014).

[12] Rusu R B, Blodow N, Beetz M. Fast point feature histograms (FPFH) for 3D registration[C], 3212-3217(2009).

[13] Salti S, Tombari F, Di Stefano L. SHOT: Unique signatures of histograms for surface and texture description[J]. Computer Vision and Image Understanding, 125, 251-264(2014).

[14] Körtgen M, Park G J, Novotni M et al. 3shape matching withD 3D shape contexts[EB/OL]. https://cg.cs.uni-bonn.de/backend/v1/files/publications/koertgen-2003-3d.pdf

[15] Zhou Q Y, Park J, Koltun V. Fast global registration[M]. Computer vision-ECCV 2016, 9906, 766-782(2016).

[16] Yang H, Shi J N, Carlone L. TEASER: fast and certifiable point cloud registration[J]. IEEE Transactions on Robotics, 37, 314-333(2021).

[17] Chen Z, Sun K, Yang F et al. SC2-PCR: a second order spatial compatibility for efficient and robust point cloud registration[C], 13211-13221(2022).

[18] Zhang X Y, Yang J Q, Zhang S K et al. 3D registration with maximal cliques[C], 17745-17754(2023).

[19] Choy C, Park J, Koltun V. Fully convolutional geometric features[C], 8957-8965(2019).

[20] Pais G D, Ramalingam S, Govindu V M et al. 3DRegNet: a deep neural network for 3D point registration[C], 7191-7201(2020).

[21] Choy C, Dong W, Koltun V. Deep global registration[C], 2511-2520(2020).

[22] Bai X Y, Luo Z X, Zhou L et al. PointDSC: robust point cloud registration using deep spatial consistency[C], 15854-15864(2021).

[23] Huang S Y, Gojcic Z, Usvyatsov M et al. PREDATOR: registration of 3D point clouds with low overlap[C], 4265-4274(2021).

[24] Yew Z J, Lee G H. REGTR: end-to-end point cloud correspondences with transformers[C], 6667-6676(2022).

[25] Qin Z, Yu H, Wang C J et al. GeoTransformer: fast and robust point cloud registration with geometric transformer[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45, 9806-9821(2023).

[26] Zhou H, Wang X C, Yuan Y. Three-dimensional point cloud registration network based on deep interactive multi-scale receptive field feature learning[J]. Acta Optica Sinica, 44, 1415001(2024).

[27] Geiger A, Lenz P, Urtasun R. Are we ready for autonomous driving? The KITTI vision benchmark suite[C], 3354-3361(2012).

[28] Zeng A, Song S R, Nießner M et al. 3DMatch: learning local geometric descriptors from RGB-D reconstructions[C], 199-208(2017).

[29] Eppstein D, Löffler M, Strash D. Listing all maximal cliques in sparse graphs in near-optimal time[M]. Algorithms and computation, 6506, 403-414(2010).

[30] Clemente G P, Grassi R. Directed clustering in weighted networks: a new perspective[J]. Chaos, 107, 26-38(2018).

[31] Kemper A[M]. Valuation of network effects in software markets: a complex networks approach, 140-142(2009).

[32] Sorkine-Hornung O, Rabinovich M. Least-squares rigid motion using SVD[EB/OL]. https://igl.ethz.ch/projects/ARAP/svd_rot.pdf

[33] Yang J Q, Huang Z Q, Quan S W et al. Toward efficient and robust metrics for RANSAC hypotheses and 3D rigid registration[J]. IEEE Transactions on Circuits and Systems for Video Technology, 32, 893-906(2022).

[34] Sattler T, Maddern W, Toft C et al. Benchmarking 6DOF outdoor visual localization in changing conditions[C], 8601-8610(2018).

Tools

Get Citation

Copy Citation Text

Yaochang Tan, Junwei Yang, Kunyang Li, Lixin Tang. Point Cloud Registration Algorithm Based on Angle Constraint and Maximal Clique[J]. Laser & Optoelectronics Progress, 2025, 62(12): 1215012

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites